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django-recommender-search-backend-patterns

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Django backend patterns for recommendation services (AWS Personalize, Databricks Model Serving, internal microservices) and OpenSearch-backed search/feed endpoints. Covers fan-out orchestration (asyncio.gather, deadline propagation, partial results, async client reuse), external service protection (timeouts, circuit breakers, jittered retry, bulkheads, rate limits), OpenSearch query patterns (search_after, _source filtering, function_score, aliases, routing, bool.filter), result blending (score normalization, MMR, dedup, cold-start), Redis caching (stampede protection, model-versioned keys, two-tier, negative), resilience (partial-response envelope, stale-on-error, graceful degradation), async (sync_to_async, async ORM, uvicorn, contextvars, disconnect cancellation), and DRF response shape (cursor pagination, ETag, throttling). Use when building, reviewing, or refactoring such a Django backend. Triggers even without explicit "scale" cues. Includes 5 scaffolding templates.

skills/.experimental/django-recommender-search-backend-patterns/SKILL.md

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# Experimental Django Recommender + Search Backend Best Practices

Implementation patterns for a Django backend serving mixed-results recommendations (Personalize / Databricks / microservice fan-out) and OpenSearch-backed search/feeds. **48 rules across 8 categories**, ordered by execution lifecycle impact — earlier categories cascade through everything downstream.

This is the *backend* peer of the `react-fetch-cache-patterns` skill. React handles client-side waterfalls and caching; this skill handles server-side fan-out, downstream protection, OpenSearch query design, and ML-blend orchestration.

## When to Apply

- Building or reviewing Django views that fan out to AWS Personalize, Databricks Model Serving, internal microservices, or any ML inference downstream
- Designing OpenSearch query endpoints (search results, infinite feeds, faceted search)
- Implementing a recommendations endpoint that blends multiple ranker outputs
- Investigating "Django backend slow when downstream is degraded" or "Personalize quota exhausted"
- Adding caching, retry, circuit breakers, or rate limiting to outbound calls
- Choosing between sync and async Django views, configuring uvicorn vs gunicorn
- Designing DRF response shapes for paginated feeds, partial results, or degraded paths
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